Category Archives: change management

A vanquished ghost returns as details of distress required in NHS opt out

It seems the ugly ghosts of care.data past were alive and well at NHS Digital this Christmas.

Old style thinking, the top-down patriarchal ‘no one who uses a public service should be allowed to opt out of sharing their records. Nor can people rely on their record being anonymised,‘ that you thought was vanquished, has returned with a vengeance.

The Secretary of State for Health, Jeremy Hunt, has reportedly  done a U-turn on opt out of the transfer of our medical records to third parties without consent.

That backtracks on what he said in Parliament on January 25th, 2014 on opt out of anonymous data transfers, despite the right to object in the NHS constitution [1].

So what’s the solution? If the new opt out methods aren’t working, then back to the old ones and making Section 10 requests? But it seems the Information Centre isn’t keen on making that work either.

All the data the HSCIC holds is sensitive and as such, its release risks patients’ significant harm or distress [2] so it shouldn’t be difficult to tell them to cease and desist, when it comes to data about you.

But how is NHS Digital responding to people who make the effort to write directly?

Someone who “got a very unhelpful reply” is being made to jump through hoops.

If anyone asks that their hospital data should not be used in any format and passed to third parties, that’s surely for them to decide.

Let’s take the case study of a woman who spoke to me during the whole care.data debacle who had been let down by the records system after rape. Her NHS records subsequently about her mental health care were inaccurate, and had led to her being denied the benefit of private health insurance at a new job.

Would she have to detail why selling her medical records would cause her distress? What level of detail is fair and who decides? The whole point is, you want to keep info confidential.

Should you have to state what you fear? “I have future distress, what you might do to me?” Once you lose control of data, it’s gone. Based on past planning secrecy and ideas for the future, like mashing up health data with retail loyalty cards as suggested at Strata in November 2013 [from 16:00] [2] no wonder people are sceptical. 

Given the long list of commercial companies,  charities, think tanks and others that passing out our sensitive data puts at risk and given the Information Centre’s past record, HSCIC might be grateful they have only opt out requests to deal with, and not millions of medical ethics court summonses. So far.

HSCIC / NHS Digital has extracted our identifiable records and has given them away, including for commercial product use, and continues give them away, without informing us. We’ve accepted Ministers’ statements and that a solution would be found. Two years on, patience wears thin.

“Without that external trust, we risk losing our public mandate and then cannot offer the vital insights that quality healthcare requires.”

— Sir Nick Partridge on publication of the audit report of 10% of 3,059 releases by the HSCIC between 2005-13

— Andy WIlliams said, “We want people to be certain their choices will be followed.”

Jeremy Hunt said everyone should be able to opt out of having their anonymised data used. David Cameron did too when the plan was  announced in 2012.

In 2014 the public was told there should be no more surprises. This latest response is not only a surprise but enormously disrespectful.

When you’re trying to rebuild trust, assuming that we accept that ‘is’ the aim, you can’t say one thing, and do another.  Perhaps the Department for Health doesn’t like the public answer to what the public wants from opt out, but that doesn’t make the DH view right.

Perhaps NHS Digital doesn’t want to deal with lots of individual opt out requests, that doesn’t make their refusal right.

Kingsley Manning recognised in July 2014, that the Information Centre “had made big mistakes over the last 10 years.” And there was “a once-in-a-generation chance to get it right.”

I didn’t think I’d have to move into the next one before they fix it.

The recent round of 2016 public feedback was the same as care.data 1.0. Respect nuanced opt outs and you will have all the identifiable public interest research data you want. Solutions must be better for other uses, opt out requests must be respected without distressing patients further in the process, and anonymous must mean  anonymous.

Pseudonymised data requests that go through the DARS process so that a Data Sharing Framework Contract and Data Sharing Agreement are in place are considered to be compliant with the ICO code of practice – fine, but they are not anonymous. If DARS is still giving my family’s data to Experian, Harvey Walsh, and co, despite opt out, I’ll be furious.

The [Caldicott 2] Review Panel found “that commissioners do not need dispensation from confidentiality, human rights & data protection law.

Neither do our politicians, their policies or ALBs.


[1] https://www.england.nhs.uk/ourwork/tsd/ig/ig-fair-process/further-info-gps/

“A patient can object to their confidential personal information from being disclosed out of the GP Practice and/or from being shared onwards by the HSCIC for non-direct care purposes (secondary purposes).”

[2] Minimum Mandatory Measures http://www.nationalarchives.gov.uk/documents/information-management/cross-govt-actions.pdf p7

care.data listening events and consultation: The same notes again?

If lots of things get said in a programme of events, and nothing is left around to read about it, did they happen?

The care.data programme 2014-15 listening exercise and action plan has become impossible to find online. That’s OK, you might think, the programme has been scrapped. Not quite.

You can give your views online until September 7th on the new consultation, “New data security standards and opt-out models for health and social care”  and/or attend the new listening events, September 26th in London, October 3rd in Southampton and October 10th in Leeds.

The Ministerial statement on July 6, announced that NHS England had taken the decision to close the care.data programme after the review of data security and consent by Dame Fiona Caldicott, the National Data Guardian for Health and Care.

But the same questions are being asked again around consent and use of your medical data, from primary and secondary care. What a very long questionnaire asks is in effect,  do you want to keep your medical history private? You can answer only Q 15 if you want.

Ambiguity again surrounds what constitutes “de-identified” patient information.

What is clear is that public voice seems to have been deleted or lost from the care.data programme along with the feedback and brand.

People spoke up in 2014, and acted. The opt out that 1 in 45 people chose between January and March 2014 was put into effect by the HSCIC in April 2016. Now it seems, that might be revoked.

We’ve been here before.  There is no way that primary care data can be extracted without consent without it causing further disruption and damage to public trust and public interest research.  The future plans for linkage between all primary care data and secondary data and genomics for secondary uses, is untenable without consent.

Upcoming events cost time and money and will almost certainly go over the same ground that hours and hours were spent on in 2014. However if they do achieve a meaningful response rate, then I hope the results will not be lost and will be combined with those already captured under the ‘care.data listening events’ responses.  Will they have any impact on what consent model there may be in future?

So what we gonna do? I don’t know, whatcha wanna do? Let’s do something.

Let’s have accredited access and security fixed. While there may now be a higher transparency and process around release, there are still problems about who gets data and what they do with it.

Let’s have clear future scope and control. There is still no plan to give the public rights to control or delete data if we change our minds who can have it or for what purposes. And that is very uncertain. After all, they might decide to privatise or outsource the whole thing as was planned for the CSUs. 

Let’s have answers to everything already asked but unknown. The questions in the previous Caldicott review have still to be answered.

We have the possibility to  see health data used wisely, safely, and with public trust. But we seem stuck with the same notes again. And the public seem to be the last to be invited to participate and views once gathered, seem to be disregarded. I hope to be proved wrong.

Might, perhaps, the consultation deliver the nuanced consent model discussed at public listening exercises that many asked for?

Will the care.data listening events feedback summary be found, and will its 2014 conclusions and the enacted opt out be ignored? Will the new listening event view make more difference than in 2014?

Is public engagement, engagement, if nobody hears what was said?

Mum, are we there yet? Why should AI care.

Mike Loukides drew similarities between the current status of AI and children’s learning in an article I read this week.

The children I know are always curious to know where they are going, how long will it take, and how they will know when they get there. They ask others for guidance often.

Loukides wrote that if you look carefully at how humans learn, you see surprisingly little unsupervised learning.

If unsupervised learning is a prerequisite for general intelligence, but not the substance, what should we be looking for, he asked. It made me wonder is it also true that general intelligence is a prerequisite for unsupervised learning? And if so, what level of learning must AI achieve before it is capable of recursive self-improvement? What is AI being encouraged to look for as it learns, what is it learning as it looks?

What is AI looking for and how will it know when it gets there?

Loukides says he can imagine a toddler learning some rudiments of counting and addition on his or her own, but can’t imagine a child developing any sort of higher mathematics without a teacher.

I suggest a different starting point. I think children develop on their own, given a foundation. And if the foundation is accompanied by a purpose — to understand why they should learn to count, and why they should want to — and if they have the inspiration, incentive and  assets they’ll soon go off on their own, and outstrip your level of knowledge. That may or may not be with a teacher depending on what is available, cost, and how far they get compared with what they want to achieve.

It’s hard to learn something from scratch by yourself if you have no boundaries to set knowledge within and search for more, or to know when to stop when you have found it.

You’ve only to start an online course, get stuck, and try to find the solution through a search engine to know how hard it can be to find the answer if you don’t know what you’re looking for. You can’t type in search terms if you don’t know the right words to describe the problem.

I described this recently to a fellow codebar-goer, more experienced than me, and she pointed out something much better to me. Don’t search for the solution or describe what you’re trying to do, ask the search engine to find others with the same error message.

In effect she said, your search is wrong. Google knows the answer, but can’t tell you what you want to know, if you don’t ask it in the way it expects.

So what will AI expect from people and will it care if we dont know how to interrelate? How does AI best serve humankind and defined by whose point-of-view? Will AI serve only those who think most closely in AI style steps and language?  How will it serve those who don’t know how to talk about, or with it? AI won’t care if we don’t.

If as Loukides says, we humans are good at learning something and then applying that knowledge in a completely different area, it’s worth us thinking about how we are transferring our knowledge today to AI and how it learns from that. Not only what does AI learn in content and context, but what does it learn about learning?

His comparison of a toddler learning from parents — who in effect are ‘tagging’ objects through repetition of words while looking at images in a picture book — made me wonder how we will teach AI the benefit of learning? What incentive will it have to progress?

“the biggest project facing AI isn’t making the learning process faster and more efficient. It’s moving from machines that solve one problem very well (such as playing Go or generating imitation Rembrandts) to machines that are flexible and can solve many unrelated problems well, even problems they’ve never seen before.”

Is the skill to enable “transfer learning” what will matter most?

For AI to become truly useful, we need better as a global society to understand *where* it might best interface with our daily lives, and most importantly *why*.  And consider *who* is teaching and AI and who is being left out in the crowdsourcing of AI’s teaching.

Who is teaching AI what it needs to know?

The natural user interfaces for people to interact with today’s more common virtual assistants (Amazon’s Alexa, Apple’s Siri and Viv, Microsoft  and Cortana) are not just providing information to the user, but through its use, those systems are learning. I wonder what percentage of today’s  population is using these assistants, how representative are they, and what our AI assistants are being taught through their use? Tay was a swift lesson learned for Microsoft.

In helping shape what AI learns, what range of language it will use to develop its reference words and knowledge, society co-shapes what AI’s purpose will be —  and for AI providers to know what’s the point of selling it. So will this technology serve everyone?

Are providers counter-balancing what AI is currently learning from crowdsourcing, if the crowd is not representative of society?

So far we can only teach machines to make decisions based on what we already know, and what we can tell it to decide quickly against pre-known references using lots of data. Will your next image captcha, teach AI to separate the sloth from the pain-au-chocolat?

One of the task items for machine processing is better searches. Measurable goal driven tasks have boundaries, but who sets them? When does a computer know, if it’s found enough to make a decision. If the balance of material about the Holocaust on the web for example, were written by Holocaust deniers will AI know who is right? How will AI know what is trusted and by whose measure?

What will matter most is surely not going to be how to optimise knowledge transfer from human to AI — that is the baseline knowledge of supervised learning — and it won’t even be for AI to know when to use its skill set in one place and when to apply it elsewhere in a different context; so-called learning transfer, as Mike Loukides says. But rather, will AI reach the point where it cares?

  • Will AI ever care what it should know and where to stop or when it knows enough on any given subject?
  • How will it know or care if what it learns is true?
  • If in the best interests of advancing technology or through inaction  we do not limit its boundaries, what oversight is there of its implications?

Online limits will limit what we can reach in Thinking and Learning

If you look carefully at how humans learn online, I think rather than seeing  surprisingly little unsupervised learning, you see a lot of unsupervised questioning. It is often in the questioning that is done in private we discover, and through discovery we learn. Often valuable discoveries are made; whether in science, in maths, or important truths are found where there is a need to challenge the status quo. Imagine if Galileo had given up.

The freedom to think freely and to challenge authority, is vital to protect, and one reason why I and others are concerned about the compulsory web monitoring starting on September 5th in all schools in England, and its potential chilling effect. Some are concerned who  might have access to these monitoring results today or in future, if stored could they be opened to employers or academic institutions?

If you tell children do not use these search terms and do not be curious about *this* subject without repercussions, it is censorship. I find the idea bad enough for children, but for us as adults its scary.

As Frankie Boyle wrote last November, we need to consider what our internet history is:

“The legislation seems to view it as a list of actions, but it’s not. It’s a document that shows what we’re thinking about.”

Children think and act in ways that they may not as an adult. People also think and act differently in private and in public. It’s concerning that our private online activity will become visible to the State in the IP Bill — whether photographs that captured momentary actions in social media platforms without the possibility to erase them, or trails of transitive thinking via our web history — and third-parties may make covert judgements and conclusions about us, correctly or not, behind the scenes without transparency, oversight or recourse.

Children worry about lack of recourse and repercussions. So do I. Things done in passing, can take on a permanence they never had before and were never intended. If expert providers of the tech world such as Apple Inc, Facebook Inc, Google Inc, Microsoft Corp, Twitter Inc and Yahoo Inc are calling for change, why is the government not listening? This is more than very concerning, it will have disastrous implications for trust in the State, data use by others, self-censorship, and fear that it will lead to outright censorship of adults online too.

By narrowing our parameters what will we not discover? Not debate?  Or not invent? Happy are the clockmakers, and kids who create. Any restriction on freedom to access information, to challenge and question will restrict children’s learning or even their wanting to.  It will limit how we can improve our shared knowledge and improve our society as a result. The same is true of adults.

So in teaching AI how to learn, I wonder how the limitations that humans put on its scope — otherwise how would it learn what the developers want — combined with showing it ‘our thinking’ through search terms,  and how limitations on that if users self-censor due to surveillance, will shape what AI will help us with in future and will it be the things that could help the most people, the poorest people, or will it be people like those who programme the AI and use search terms and languages it already understands?

Who is accountable for the scope of what we allow AI to do or not? Who is accountable for what AI learns about us, from our behaviour data if it is used without our knowledge?

How far does AI have to go?

The leap for AI will be if and when AI can determine what it doesn’t know, and it sees a need to fill that gap. To do that, AI will need to discover a purpose for its own learning, indeed for its own being, and be able to do so without limitation from the that humans shaped its framework for doing so. How will AI know what it needs to know and why? How will it know, what it knows is right and sources to trust? Against what boundaries will AI decide what it should engage with in its learning, who from and why? Will it care? Why will it care? Will it find meaning in its reason for being? Why am I here?

We assume AI will know better. We need to care, if AI is going to.

How far are we away from a machine that is capable of recursive self-improvement, asks John Naughton in yesterday’s Guardian, referencing work by Yuval Harari suggesting artificial intelligence and genetic enhancements will usher in a world of inequality and powerful elites. As I was finishing this, I read his article, and found myself nodding, as I read the implications of new technology focus too much on technology and too little on society’s role in shaping it.

AI at the moment has a very broad meaning to the general public. Is it living with life-supporting humanoids?  Do we consider assistive search tools as AI? There is a fairly general understanding of “What is A.I., really?” Some wonder if we are “probably one of the last generations of Homo sapiens,” as we know it.

If the purpose of AI is to improve human lives, who defines improvement and who will that improvement serve? Is there a consensus on the direction AI should and should not take, and how far it should go? What will the global language be to speak AI?

As AI learning progresses, every time AI turns to ask its creators, “Are we there yet?”,  how will we know what to say?

image: Stephen Barling flickr.com/photos/cripsyduck (CC BY-NC 2.0)

OkCupid and Google DeepMind: Happily ever after? Purposes and ethics in datasharing

This blog post is also available as an audio file on soundcloud.


What constitutes the public interest must be set in a universally fair and transparent ethics framework if the benefits of research are to be realised – whether in social science, health, education and more – that framework will provide a strategy to getting the pre-requisite success factors right, ensuring research in the public interest is not only fit for the future, but thrives. There has been a climate change in consent. We need to stop talking about barriers that prevent datasharing  and start talking about the boundaries within which we can.

What is the purpose for which I provide my personal data?

‘We use math to get you dates’, says OkCupid’s tagline.

That’s the purpose of the site. It’s the reason people log in and create a profile, enter their personal data and post it online for others who are looking for dates to see. The purpose, is to get a date.

When over 68K OkCupid users registered for the site to find dates, they didn’t sign up to have their identifiable data used and published in ‘a very large dataset’ and onwardly re-used by anyone with unregistered access. The users data were extracted “without the express prior consent of the user […].”

Are the registration consent purposes compatible with the purposes to which the researcher put the data should be a simple enough question.  Are the research purposes what the person signed up to, or would they be surprised to find out their data were used like this?

Questions the “OkCupid data snatcher”, now self-confessed ‘non-academic’ researcher, thought unimportant to consider.

But it appears in the last month, he has been in good company.

Google DeepMind, and the Royal Free, big players who do know how to handle data and consent well, paid too little attention to the very same question of purposes.

The boundaries of how the users of OkCupid had chosen to reveal information and to whom, have not been respected in this project.

Nor were these boundaries respected by the Royal Free London trust that gave out patient data for use by Google DeepMind with changing explanations, without clear purposes or permission.

The legal boundaries in these recent stories appear unclear or to have been ignored. The privacy boundaries deemed irrelevant. Regulatory oversight lacking.

The respectful ethical boundaries of consent to purposes, disregarding autonomy, have indisputably broken down, whether by commercial org, public body, or lone ‘researcher’.

Research purposes

The crux of data access decisions is purposes. What question is the research to address – what is the purpose for which the data will be used? The intent by Kirkegaard was to test:

“the relationship of cognitive ability to religious beliefs and political interest/participation…”

In this case the question appears intended rather a test of the data, not the data opened up to answer the test. While methodological studies matter, given the care and attention [or self-stated lack thereof] given to its extraction and any attempt to be representative and fair, it would appear this is not the point of this study either.

The data doesn’t include profiles identified as heterosexual male, because ‘the scraper was’. It is also unknown how many users hide their profiles, “so the 99.7% figure [identifying as binary male or female] should be cautiously interpreted.”

“Furthermore, due to the way we sampled the data from the site, it is not even representative of the users on the site, because users who answered more questions are overrepresented.” [sic]

The paper goes on to say photos were not gathered because they would have taken up a lot of storage space and could be done in a future scraping, and

“other data were not collected because we forgot to include them in the scraper.”

The data are knowingly of poor quality, inaccurate and incomplete. The project cannot be repeated as ‘the scraping tool no longer works’. There is an unclear ethical or peer review process, and the research purpose is at best unclear. We can certainly give someone the benefit of the doubt and say intent appears to have been entirely benevolent. It’s not clear what the intent was. I think it is clearly misplaced and foolish, but not malevolent.

The trouble is, it’s not enough to say, “don’t be evil.” These actions have consequences.

When the researcher asserts in his paper that, “the lack of data sharing probably slows down the progress of science immensely because other researchers would use the data if they could,”  in part he is right.

Google and the Royal Free have tried more eloquently to say the same thing. It’s not research, it’s direct care, in effect, ignore that people are no longer our patients and we’re using historical data without re-consent. We know what we’re doing, we’re the good guys.

However the principles are the same, whether it’s a lone project or global giant. And they’re both wildly wrong as well. More people must take this on board. It’s the reason the public interest needs the Dame Fiona Caldicott review published sooner rather than later.

Just because there is a boundary to data sharing in place, does not mean it is a barrier to be ignored or overcome. Like the registration step to the OkCupid site, consent and the right to opt out of medical research in England and Wales is there for a reason.

We’re desperate to build public trust in UK research right now. So to assert that the lack of data sharing probably slows down the progress of science is misplaced, when it is getting ‘sharing’ wrong, that caused the lack of trust in the first place and harms research.

A climate change in consent

There has been a climate change in public attitude to consent since care.data, clouded by the smoke and mirrors of state surveillance. It cannot be ignored.  The EUGDPR supports it. Researchers may not like change, but there needs to be an according adjustment in expectations and practice.

Without change, there will be no change. Public trust is low. As technology advances and if we continue to see commercial companies get this wrong, we will continue to see public trust falter unless broken things get fixed. Change is possible for the better. But it has to come from companies, institutions, and people within them.

Like climate change, you may deny it if you choose to. But some things are inevitable and unavoidably true.

There is strong support for public interest research but that is not to be taken for granted. Public bodies should defend research from being sunk by commercial misappropriation if they want to future-proof public interest research.

The purpose for which the people gave consent are the boundaries within which you have permission to use data, that gives you freedom within its limits, to use the data.  Purposes and consent are not barriers to be overcome.

If research is to win back public trust developing a future proofed, robust ethical framework for data science must be a priority today.

Commercial companies must overcome the low levels of public trust they have generated in the public to date if they ask ‘trust us because we’re not evil‘. If you can’t rule out the use of data for other purposes, it’s not helping. If you delay independent oversight it’s not helping.

This case study and indeed the Google DeepMind recent episode by contrast demonstrate the urgency with which working out what common expectations and oversight of applied ethics in research, who gets to decide what is ‘in the public interest’ and data science public engagement must be made a priority, in the UK and beyond.

Boundaries in the best interest of the subject and the user

Society needs research in the public interest. We need good decisions made on what will be funded and what will not be. What will influence public policy and where needs attention for change.

To do this ethically, we all need to agree what is fair use of personal data, when is it closed and when is it open, what is direct and what are secondary uses, and how advances in technology are used when they present both opportunities for benefit or risks to harm to individuals, to society and to research as a whole.

The potential benefits of research are potentially being compromised for the sake of arrogance, greed, or misjudgement, no matter intent. Those benefits cannot come at any cost, or disregard public concern, or the price will be trust in all research itself.

In discussing this with social science and medical researchers, I realise not everyone agrees. For some, using deidentified data in trusted third party settings poses such a low privacy risk, that they feel the public should have no say in whether their data are used in research as long it’s ‘in the public interest’.

For the DeepMind researchers and Royal Free, they were confident even using identifiable data, this is the “right” thing to do, without consent.

For the Cabinet Office datasharing consultation, the parts that will open up national registries, share identifiable data more widely and with commercial companies, they are convinced it is all the “right” thing to do, without consent.

How can researchers, society and government understand what is good ethics of data science, as technology permits ever more invasive or covert data mining and the current approach is desperately outdated?

Who decides where those boundaries lie?

“It’s research Jim, but not as we know it.” This is one aspect of data use that ethical reviewers will need to deal with, as we advance the debate on data science in the UK. Whether independents or commercial organisations. Google said their work was not research. Is‘OkCupid’ research?

If this research and data publication proves anything at all, and can offer lessons to learn from, it is perhaps these three things:

Who is accredited as a researcher or ‘prescribed person’ matters. If we are considering new datasharing legislation, and for example, who the UK government is granting access to millions of children’s personal data today. Your idea of a ‘prescribed person’ may not be the same as the rest of the public’s.

Researchers and ethics committees need to adjust to the climate change of public consent. Purposes must be respected in research particularly when sharing sensitive, identifiable data, and there should be no assumptions made that differ from the original purposes when users give consent.

Data ethics and laws are desperately behind data science technology. Governments, institutions, civil, and all society needs to reach a common vision and leadership how to manage these challenges. Who defines these boundaries that matter?

How do we move forward towards better use of data?

Our data and technology are taking on a life of their own, in space which is another frontier, and in time, as data gathered in the past might be used for quite different purposes today.

The public are being left behind in the game-changing decisions made by those who deem they know best about the world we want to live in. We need a say in what shape society wants that to take, particularly for our children as it is their future we are deciding now.

How about an ethical framework for datasharing that supports a transparent public interest, which tries to build a little kinder, less discriminating, more just world, where hope is stronger than fear?

Working with people, with consent, with public support and transparent oversight shouldn’t be too much to ask. Perhaps it is naive, but I believe that with an independent ethical driver behind good decision-making, we could get closer to datasharing like that.

That would bring Better use of data in government.

Purposes and consent are not barriers to be overcome. Within these, shaped by a strong ethical framework, good data sharing practices can tackle some of the real challenges that hinder ‘good use of data’: training, understanding data protection law, communications, accountability and intra-organisational trust. More data sharing alone won’t fix these structural weaknesses in current UK datasharing which are our really tough barriers to good practice.

How our public data will be used in the public interest will not be a destination or have a well defined happy ending, but it is a long term  process which needs to be consensual and there needs to be a clear path to setting out together and achieving collaborative solutions.

While we are all different, I believe that society shares for the most part, commonalities in what we accept as good, and fair, and what we believe is important. The family sitting next to me have just counted out their money and bought an ice cream to share, and the staff gave them two. The little girl is beaming. It seems that even when things are difficult, there is always hope things can be better. And there is always love.

Even if some might give it a bad name.

********

img credit: flickr/sofi01/ Beauty and The Beast  under creative commons

Can new datasharing laws win social legitimacy, public trust and support without public engagement?

I’ve been struck by stories I’ve heard on the datasharing consultation, on data science, and on data infrastructures as part of ‘government as a platform’ (#GaaPFuture) in recent weeks. The audio recorded by the Royal Statistical Society on March 17th is excellent, and there were some good questions asked.

There were even questions from insurance backed panels to open up more data for commercial users, and calls for journalists to be seen as accredited researchers, as well as to include health data sharing. Three things that some stakeholders, all users of data, feel are  missing from consultation, and possibly some of those with the most widespread public concern and lowest levels of public trust. [1]

What I feel is missing in consultation discussions are:

  1. a representative range of independent public voice
  2. a compelling story of needs – why tailored public services benefits citizens from whom data is taken, not only benefits data users
  3. the impacts we expect to see in local government
  4. any cost/risk/benefit assessment of those impacts, or for citizens
  5. how the changes will be independently evaluated – as some are to be reviewed

The Royal Statistical Society and ODI have good summaries here of their thoughts, more geared towards the statistical and research aspects of data,  infrastructure and the consultation.

I focus on the other strands that use identifiable data for targeted interventions. Tailored public services, Debt, Fraud, Energy Companies’ use. I think we talk too little of people, and real needs.

Why the State wants more datasharing is not yet a compelling story and public need and benefit seem weak.

So far the creation of new data intermediaries, giving copies of our personal data to other public bodies  – and let’s be clear that this often means through commercial representatives like G4S, Atos, Management consultancies and more –  is yet to convince me of true public needs for the people, versus wants from parts of the State.

What the consultation hopes to achieve, is new powers of law, to give increased data sharing increased legal authority. However this alone will not bring about the social legitimacy of datasharing that the consultation appears to seek through ‘open policy making’.

Legitimacy is badly needed if there is to be public and professional support for change and increased use of our personal data as held by the State, which is missing today,  as care.data starkly exposed. [2]

The gap between Social Legitimacy and the Law

Almost 8 months ago now, before I knew about the datasharing consultation work-in-progress, I suggested to BIS that there was an opportunity for the UK to drive excellence in public involvement in the use of public data by getting real engagement, through pro-active consent.

The carrot for this, is achieving the goal that government wants – greater legal clarity, the use of a significant number of consented people’s personal data for complex range of secondary uses as a secondary benefit.

It was ignored.

If some feel entitled to the right to infringe on citizens’ privacy through a new legal gateway because they believe the public benefit outweighs private rights, then they must also take on the increased balance of risk of doing so, and a responsibility to  do so safely. It is in principle a slippery slope. Any new safeguards and ethics for how this will be done are however unclear in those data strands which are for targeted individual interventions. Especially if predictive.

Upcoming discussions on codes of practice [which have still to be shared] should demonstrate how this is to happen in practice, but codes are not sufficient. Laws which enable will be pushed to their borderline of legal and beyond that of ethical.

In England who would have thought that the 2013 changes that permitted individual children’s data to be given to third parties [3] for educational purposes, would mean giving highly sensitive, identifiable data to journalists without pupils or parental consent? The wording allows it. It is legal. However it fails the DPA Act legal requirement of fair processing.  Above all, it lacks social legitimacy and common sense.

In Scotland, there is current anger over the intrusive ‘named person’ laws which lack both professional and public support and intrude on privacy. Concerns raised should be lessons to learn from in England.

Common sense says laws must take into account social legitimacy.

We have been told at the open policy meetings that this change will not remove the need for informed consent. To be informed, means creating the opportunity for proper communications, and also knowing how you can use the service without coercion, i.e. not having to consent to secondary data uses in order to get the service, and knowing to withdraw consent at any later date. How will that be offered with ways of achieving the removal of data after sharing?

The stick for change, is the legal duty that the recent 2015 CJEU ruling reiterating the legal duty to fair processing [4] waved about. Not just a nice to have, but State bodies’ responsibility to inform citizens when their personal data are used for purposes other than those for which those data had initially been consented and given. New legislation will not  remove this legal duty.

How will it be achieved without public engagement?

Engagement is not PR

Failure to act on what you hear from listening to the public is costly.

Engagement is not done *to* people, don’t think explain why we need the data and its public benefit’ will work. Policy makers must engage with fears and not seek to dismiss or diminish them, but acknowledge and mitigate them by designing technically acceptable solutions. Solutions that enable data sharing in a strong framework of privacy and ethics, not that sees these concepts as barriers. Solutions that have social legitimacy because people support them.

Mr Hunt’s promised February 2014 opt out of anonymised data being used in health research, has yet to be put in place and has had immeasurable costs for delayed public research, and public trust.

How long before people consider suing the DH as data controller for misuse? From where does the arrogance stem that decides to ignore legal rights, moral rights and public opinion of more people than those who voted for the Minister responsible for its delay?

 

This attitude is what fails care.data and the harm is ongoing to public trust and to confidence for researchers’ continued access to data.

The same failure was pointed out by the public members of the tiny Genomics England public engagement meeting two years ago in March 2014, called to respond to concerns over the lack of engagement and potential harm for existing research. The comms lead made a suggestion that the new model of the commercialisation of the human genome in England, to be embedded in the NHS by 2017 as standard clinical practice, was like steam trains in Victorian England opening up the country to new commercial markets. The analogy was felt by the lay attendees to be, and I quote, ‘ridiculous.’

Exploiting confidential personal data for public good must have support and good two-way engagement if it is to get that support, and what is said and agreed must be acted on to be trustworthy.

Policy makers must take into account broad public opinion, and that is unlikely to be submitted to a Parliamentary consultation. (Personally, I first knew such  processes existed only when care.data was brought before the Select Committee in 2014.) We already know what many in the public think about sharing their confidential data from the work with care.data and objections to third party access, to lack of consent. Just because some policy makers don’t like what was said, doesn’t make that public opinion any less valid.

We must bring to the table the public voice from past but recent public engagement work on administrative datasharing [5], the voice of the non-research community, and from those who are not stakeholders who will use the data but the ‘data subjects’, the public  whose data are to be used.

Policy Making must be built on Public Trust

Open policy making is not open just because it says it is. Who has been invited, participated, and how their views actually make a difference on content and implementation is what matters.

Adding controversial ideas at the last minute is terrible engagement, its makes the process less trustworthy and diminishes its legitimacy.

This last minute change suggests some datasharing will be dictated despite critical views in the policy making and without any public engagement. If so, we should ask policy makers on what mandate?

Democracy depends on social legitimacy. Once you lose public trust, it is not easy to restore.

Can new datasharing laws win social legitimacy, public trust and support without public engagement?

In my next post I’ll post look at some of the public engagement work done on datasharing to date, and think about ethics in how data are applied.

*************

References:

[1] The Royal Statistical Society data trust deficit

[2] “The social licence for research: why care.data ran into trouble,” by Carter et al.

[3] FAQs: Campaign for safe and ethical National Pupil Data

[4] CJEU Bara 2015 Ruling – fair processing between public bodies

[5] Public Dialogues using Administrative data (ESRC / ADRN)

img credit: flickr.com/photos/internetarchivebookimages/

A data sharing fairytale (3): transformation and impact

Part three: It is vital that the data sharing consultation is not seen in a silo, or even a set of silos each particular to its own stakeholder. To do it justice and ensure the questions that should be asked are answered, we must look instead at the whole story and the background setting. And we must ask each stakeholder, what does your happy ending look like?

Parts one and two to follow address public engagement and ethics, this focuses on current national data practice, tailored public services, and local impact of the change and transformation that will result.

What is your happy ending?

This data sharing consultation is gradually revealing to me how disjoined government appears in practice and strategy. Our digital future, a society that is more inclusive and more just, supported by better uses of technology and data in ‘dot everyone’ will not happen if they cannot first join the dots across all of Cabinet thinking and good practice, and align policies that are out of step with each other.

Last Thursday night’s “Government as a Platform Future” panel discussion (#GaaPFuture) took me back to memories of my old job, working in business implementations of process and cutting edge systems. Our finest hour was showing leadership why success would depend on neither. Success was down to local change management and communications, because change is about people, not the tech.

People in this data sharing consultation, means the public, means the staff of local government public bodies, as well as the people working at national stakeholders of the UKSA (statistics strand), ADRN (de-identified research strand), Home Office (GRO strand), DWP (Fraud and Debt strands), and DECC (energy) and staff at the national driver, the Cabinet Office.

I’ve attended two of the 2016 datasharing meetings,  and am most interested from three points of view  – because I am directly involved in the de-identified data strand,  campaign for privacy, and believe in public engagement.

Engagement with civil society, after almost 2 years of involvement on three projects, and an almost ten month pause in between, the projects had suddenly become six in 2016, so the most sensitive strands of the datasharing legislation have been the least openly discussed.

At the end of the first 2016 meeting, I asked one question.

How will local change management be handled and the consultation tailored to local organisations’ understanding and expectations of its outcome?

Why? Because a top down data extraction programme from all public services opens up the extraction of personal data as business intelligence to national level, of all local services interactions with citizens’ data.  Or at least, those parts they have collected or may collect in future.

That means a change in how the process works today. Global business intelligence/data extractions are designed to make processes more efficient, through reductions in current delivery, yet concrete public benefits for citizens are hard to see that would be different from today, so why make this change in practice?

What it might mean for example, would be to enable collection of all citizens’ debt information into one place, and that would allow the service to centralise chasing debt and enforce its collection, outsourced to a single national commercial provider.

So what does the future look like from the top? What is the happy ending for each strand, that will be achieved should this legislation be passed?  What will success for each set of plans look like?

What will we stop doing, what will we start doing differently and how will services concretely change from today, the current state, to the future?

Most importantly to understand its implications for citizens and staff, we should ask how will this transformation be managed well to see the benefits we are told it will deliver?

Can we avoid being left holding a pumpkin, after the glitter of ‘use more shiny tech’ and government love affair with the promises of Big Data wear off?

Look into the local future

Those with the vision of the future on a panel at the GDS meeting this week, the new local government model enabled by GaaP, also identified, there are implications for potential loss of local jobs, and “turkeys won’t vote for Christmas”. So who is packaging this change to make it successfully deliverable?

If we can’t be told easily in consultation, then it is not a clear enough policy to deliver. If there is a clear end-state, then we should ask what the applied implications in practice are going to be?

It is vital that the data sharing consultation is not seen in a silo, or even a set of silos each particular to its own stakeholder, about copying datasets to share them more widely, but that we look instead at the whole story and the background setting.

The Tailored Reviews: public bodies guidance suggests massive reform of local government, looking for additional savings, looking to cut back office functions and commercial plans. It asks “What workforce reductions have already been agreed for the body? Is there potential to go further? Are these linked to digital savings referenced earlier?”

Options include ‘abolish, move out of central government, commercial model, bring in-house, merge with another body.’

So where is the local government public bodies engagement with change management plans in the datasharing consultation as a change process? Does it not exist?

I asked at the end of the first datasharing meeting in January and everyone looked a bit blank. A question ‘to take away’ turned into nothing.

Yet to make this work, the buy-in of local public bodies is vital. So why skirt round this issue in local government, if there are plans to address it properly?

If there are none, then with all the data in the world, public services delivery will not be improved, because the issues are friction not of interference by consent, or privacy issues, but working practices.

If the idea is to avoid this ‘friction’ by removing it, then where is the change management plan for public services and our public staff?

Trust depends on transparency

John Pullinger, our National Statistician, this week also said on datasharing we need a social charter on data to develop trust.

Trust can only be built between public and state if the organisations, and all the people in them, are trustworthy.

To implement process change successfully, the people involved in these affected organisations, the staff, must trust that change will mean positive improvement and risks explained.

For the public, what defined levels of data access, privacy protection, and scope limitation that this new consultation will permit in practice, are clearly going to be vital to define if the public will trust its purposes.

The consultation does not do this, and there is no draft code of conduct yet, and no one is willing to define ‘research’ or ‘public interest’.

Public interest models or ‘charter’ for collection and use of research data in health, concluded that ofr ethical purposes, time also mattered. Benefits must be specific, measurable, attainable, relevant and time-bound. So let’s talk about the intended end state that is to be achieved from these changes, and identify how its benefits are to meet those objectives – change without an intended end state will almost never be successful, if you don’t know start knowing what it looks like.

For public trust, that means scope boundaries. Sharing now, with today’s laws and ethics is only fully meaningful if we trust that today’s governance, ethics and safeguards will be changeable in future to the benefit of the citizen, not ever greater powers to the state at the expense of the individual. Where is scope defined?

There is very little information about where limits would be on what data could not be shared, or when it would not be possible to do so without explicit consent. Permissive powers put the onus onto the data controller to share, and given ‘a new law says you should share’ would become the mantra, it is likely to mean less individual accountability. Where are those lines to be drawn to support the staff and public, the data user and the data subject?

So to summarise, so far I have six key questions:

  • What does your happy ending look like for each data strand?
  • How will bad practices which conflict with the current consultation proposals be stopped?
  • How will the ongoing balance of use of data for government purposes, privacy and information rights be decided and by whom?
  • In what context will the ethical principles be shaped today?
  • How will the transformation from the current to that future end state be supported, paid for and delivered?
  • Who will oversee new policies and ensure good data science practices, protection and ethics are applied in practice?

This datasharing consultation is not entirely for something new, but expansion of what is done already. And in some places is done very badly.

How will the old stories and new be reconciled?

Wearing my privacy and public engagement hats, here’s an idea.

Perhaps before the central State starts collecting more, sharing more, and using more of our personal data for ‘tailored public services’ and more, the government should ask for a data amnesty?

It’s time to draw a line under bad practice.  Clear out the ethics drawers of bad historical practice, and start again, with a fresh chapter. Because current practices are not future-proofed and covering them up in the language of ‘better data ethics’ will fail.

The consultation assures us that: “These proposals are not about selling public or personal data, collecting new data from citizens or weakening the Data Protection Act 1998.”

However it does already sell out personal data from at least BIS. How will these contradictory positions across all Departments be resolved?

The left hand gives out de-identified data in safe settings for public benefit research while the right hands out over 10 million records to the Telegraph and The Times without parental or schools’ consent. Only in la-la land are these both considered ethical.

Will somebody at the data sharing meeting please ask, “when will this stop?” It is wrong. These are our individual children’s identifiable personal data. Stop giving them away to press and charities and commercial users without informed consent. It’s ludicrous. Yet it is real.

Policy makers should provide an assurance there are plans for this to change as part of this consultation.

Without it, the consultation line about commercial use, is at best disingenuous, at worst a bare cheeked lie.

“These powers will also ensure we can improve the safe handling of citizen data by bringing consistency and improved safeguards to the way it is handled.”

Will it? Show me how and I might believe it.

Privacy, it was said at the RSS event, is the biggest concern in this consultation:

“includes proposals to expand the use of appropriate and ethical data science techniques to help tailor interventions to the public”

“also to start fixing government’s data infrastructure to better support public services.”

The techniques need outlined what they mean, and practices fixed now, because many stand on shaky legal ground. These privacy issues have come about over cumulative governments of different parties in the last ten years, so the problems are non-partisan, but need practical fixes.

Today, less than transparent international agreements push ‘very far-reaching chapters on the liberalisation of data trading’ while according to the European Court of Justice these practices lack a solid legal basis.

Today our government already gives our children’s personal data to commercial third parties and sells our higher education data without informed consent, while the DfE and BIS both know they fail processing and its potential consequences: the European Court reaffirmed in 2015 “persons whose personal data are subject to transfer and processing between two public administrative bodies must be informed in advance” in Judgment in Case C-201/14.

In a time that actively cultivates universal public fear,  it is time for individuals to be brave and ask the awkward questions because you either solve them up front, or hit the problems later. The child who stood up and said The Emperor has on no clothes, was right.

What’s missing?

The consultation conversation will only be genuine, once the policy makers acknowledge and address solutions regards:

  1. those data practices that are currently unethical and must change
  2. how the tailored public services datasharing legislation will shape the delivery of government services’ infrastructure and staff, as well as the service to the individual in the public.

If we start by understanding what the happy ending looks like, we are much more likely to arrive there, and how to measure success.

The datasharing consultation engagement, the ethics of data science, and impact on data infrastructures as part of ‘government as a platform’ need seen as a whole joined up story if we are each to consider what success for us as stakeholders, looks like.

We need to call out current data failings and things that are missing, to get them fixed.

Without a strong, consistent ethical framework you risk 3 things:

  1. data misuse and loss of public trust
  2. data non-use because your staff don’t trust they’re doing it right
  3. data is becoming a toxic asset

The upcoming meetings should address this and ask practically:

  1. How the codes of conduct, and ethics, are to be shaped, and by whom, if outwith the consultation?
  2. What is planned to manage and pay for the future changes in our data infrastructures;  ie the models of local government delivery?
  3. What is the happy ending that each data strand wants to achieve through this and how will the success criteria be measured?

Public benefit is supposed to be at the heart of this change. For UK statistics, for academic public benefit research, they are clear.

For some of the other strands, local public benefits that outweigh the privacy risks and do not jeopardise public trust seem like magical unicorns dancing in the land far, far away of centralised government; hard to imagine, and even harder to capture.

*****

Part one: A data sharing fairytale: Engagement
Part two: A data sharing fairytale: Ethics
Part three: A data sharing fairytale: Impact (this post)

Tailored public bodies review: Feb 2016

img credit: Hermann Vogel illustration ‘Cinderella’

On the Boundaries of Being Human and Big Data

Atlas, the Boston Dynamics created robot, won hearts and minds this week as it stoically survived man being mean.  Our collective human response was an emotional defence of the machine, and criticism of its unfair treatment by its tester.

Some on Twitter recalled the incident of Lord of The Flies style bullying by children in Japan that led the programmers to create an algorithm for ‘abuse avoidance’.

The concepts of fairness and of decision making algorithms for ‘abuse avoidance’ are interesting from perspectives of data mining, AI and the wider access to and use of tech in general, and in health specifically.

If the decision to avoid abuse can be taken out of an individual’s human hands and are based on unfathomable amounts of big data, where are its limits applied to human behaviour and activity?

When it is decided that an individual’s decision making capability is impaired or has been forfeited their consent may be revoked in their best interest.

Who has oversight of the boundaries of what is acceptable for one person, or for an organisation, to decide what is in someone else’s best interest, or indeed, the public interest?

Where these boundaries overlap – personal abuse avoidance, individual best interest and the public interest – and how society manage them, with what oversight, is yet to be widely debated.

The public will shortly be given the opportunity to respond to plans for the expansion of administrative datasharing in England through consultation.

We must get involved and it must be the start of a debate and dialogue not simply a tick-box to a done-deal, if data derived from us are to be used as a platform for future to “achieve great results for the NHS and everyone who depends on it.”

Administering applied “abuse avoidance” and Restraining Abilities

Administrative uses and secondary research using the public’s personal data are applied not only in health, but across the board of public bodies, including big plans for tech in the justice system.

An example in the news this week of applied tech and its restraint on human behaviour was ankle monitors.  While one type was abandoned by the MOJ at a cost of £23m on the same day more funding for transdermal tags was announced in London.

The use of this technology as a monitoring tool, should not of itself be a punishment. It is said compliance is not intended to affect the dignity of individuals who are being monitored, but through the collection of personal and health data  will ensure the deprivation of alcohol – avoiding its abuse for a person’s own good and in the public interest. Is it fair?

Abstinence orders might be applied to those convicted of crimes such as assault, being drunk and disorderly and drunk driving.

We’re yet to see much discussion of how these varying degrees of integration of tech with the human body, and human enhancement will happen through robot elements in our human lives.

How will the boundaries of what is possible and desirable be determined and by whom with what oversight?

What else might be considered as harmful as alcohol to individuals and to  society? Drugs? Nictotine? Excess sugar?

As we wonder about the ethics of how humanoids will act and the aesthetics of how human they look, I wonder how humane are we being, in all our ‘public’ tech design and deployment?

Umberto Eco who died on Friday wrote in ‘The birth of ethics’ that there are universal ideas on constraints, effectively that people should not harm other people, through deprivation, restrictions or psychological torture. And that we should not impose anything on others that “diminishes or stifles our capacity to think.”

How will we as a society collectively agree what that should look like, how far some can impose on others, without consent?

Enhancing the Boundaries of Being Human

Technology might be used to impose bodily boundaries on some people, but tech can also be used for the enhancement of others. retweeted this week, the brilliant Angel Giuffria’s arm.

While the technology in this case is literally hands-on in its application, increasingly it is not the technology itself but the data that it creates or captures which enables action through data-based decision making.

Robots that are tiny may be given big responsibilities to monitor and report massive amounts of data. What if we could swallow them?

Data if analysed and understood, become knowledge.

Knowledge can be used to inform decisions and take action.

So where are the boundaries of what data may be extracted,  information collated, and applied as individual interventions?

Defining the Boundaries of “in the Public Interest”

Where are boundaries of what data may be created, stored, and linked to create a detailed picture about us as individuals, if the purpose is determined to be in the public interest?

Who decides which purposes are in the public interest? What qualifies as research purposes? Who qualifies as meeting the criteria of ‘researcher’?

How far can research and interventions go without consent?

Should security services and law enforcement agencies always be entitled to get access to individuals’ data ‘in the public interest’?

That’s something Apple is currently testing in the US.

Should research bodies always be entitled to get access to individuals’ data ‘in the public interest’?

That’s something care.data tried and failed to assume the public supported and has yet to re-test. Impossible before respecting the opt out that was promised over two years ago in March 2014.

The question how much data research bodies may be ‘entitled to’ will be tested again in the datasharing consultation in the UK.

How data already gathered are used in research may be used differently from it is when we consent to its use at colllection. How this changes over time and its potential for scope creep is seen in Education. Pupil data has gone from passive collection of name to giving it out to third parties, to use in national surveys, so far.

And what of the future?

Where is the boundary between access and use of data not in enforcement of acts already committed but in their prediction and prevention?

If you believe there should be an assumption of law enforcement access to data when data are used for prediction and prevention, what about health?

Should there be any difference between researchers’ access to data when data are used for past analysis and for use in prediction?

If ethics define the boundary between what is acceptable and where actions by one person may impose something on another that “diminishes or stifles our capacity to think” – that takes away our decision making capacity – that nudges behaviour, or acts on behaviour that has not yet happened, who decides what is ethical?

How does a public that is poorly informed about current data practices, become well enough informed to participate in the debate of how data management should be designed today for their future?

How Deeply Mined should our Personal Data be?

The application of technology, non-specific but not yet AI, was also announced this week in the Google DeepMind work in the NHS.

Its first key launch app co-founder provided a report that established the operating framework for the Behavioural Insights Team established by Prime Minister David Cameron.

A number of highly respected public figures have been engaged to act in the public interest as unpaid Independent Reviewers of Google DeepMind Health. It will be interesting to see what their role is and how transparent its workings and public engagement will be.

The recent consultation on the NHS gave overwhelming feedback that the public does not support the direction of current NHS change. Even having removed all responses associated with ‘lefty’ campaigns, concerns listed on page 11, are consistent including a request the Government “should end further involvement of the private sector in healthcare”. It appears from the response that this engagement exercise will feed little into practice.

The strength of feeling should however be a clear message to new projects that people are passionate that equal access to healthcare for all matters and that the public wants to be informed and have their voices heard.

How will public involvement be ensured as complexity increases in these healthcare add-ons and changing technology?

Will Google DeepMind pave the way to a new approach to health research? A combination of ‘nudge’ behavioural insights, advanced neural networks, Big Data and technology is powerful. How will that power be used?

I was recently told that if new research is not pushing the boundaries of what is possible and permissible then it may not be worth doing, as it’s probably been done before.

Should anything that is new that becomes possible be realised?

I wonder how the balance will be weighted in requests for patient data and their application, in such a high profile project.

Will NHS Research Ethics Committees turn down research proposals in-house in hospitals that benefit the institution or advance their reputation, or the HSCIC, ever feel able to say no to data use by Google DeepMind?

Ethics committees safeguard the rights, safety, dignity and well-being of research participants, independently of research sponsors whereas these representatives are not all independent of commercial supporters. And it has not claimed it’s trying to be an ethics panel. But oversight is certainly needed.

The boundaries of ownership between what is seen to benefit commercial and state in modern health investment is perhaps more than blurred to an untrained eye. Genomics England – the government’s flagship programme giving commercial access to the genome of 100K people –  stockholding companies, data analytics companies, genome analytic companies, genome collection, and human tissue research, commercial and academic research,  often share directors, working partnerships and funders. That’s perhaps unsurprising given such a specialist small world.

It’s exciting to think of the possibilities if, “through a focus on patient outcomes, effective oversight, and the highest ethical principles, we can achieve great results for the NHS and everyone who depends on it.”

Where will an ageing society go, if medics can successfully treat more cancer for example? What diseases will be prioritised and others left behind in what is economically most viable to prevent? How much investment will be made in diseases of the poor or in countries where governments cannot afford to fund programmes?

What will we die from instead? What happens when some causes of ‘preventative death’ are deemed more socially acceptable than others? Where might prevention become socially enforced through nudging behaviour into new socially acceptable or ethical norms?

Don’t be Evil

Given the leading edge of the company and its curiosity-by-design to see how far “can we” will reach, “don’t be evil” may be very important. But “be good” might be better. Where is that boundary?

The boundaries of what ‘being human’ means and how Big Data will decide and influence that, are unclear and changing. How will the law and regulation keep up and society be engaged in support?

Data principles such as fairness, keeping data accurate, complete and up-to-date and ensuring data are not excessive retained for no longer than necessary for the purpose are being widely ignored or exempted under the banner of ‘research’.

Can data use retain a principled approach despite this and if we accept commercial users, profit making based on public data, will those principles from academic research remain in practice?

Exempt from the obligation to give a copy of personal data to an individual on request if data are for ‘research’ purposes, data about us and our children, are extracted and stored ‘without us’. Forever. That means in a future that we cannot see, but Google DeepMind among others, is designing.

Lay understanding, and that of many climical professionals is likely to be left far behind if advanced technologies and use of big data decision-making algorithms are hidden in black boxes.

Public transparency of the use of our data and future planned purposes are needed to create trust that these purposes are wise.

Data are increasingly linked and more valuable when identifiable.

Any organisation that wants to future-proof its reputational risk will make sure data collection and use today is with consent, since future outcomes derived are likely to be in interventions for individuals or society. Catching up consent will be hard unless designed in now.

A Dialogue on the Boundaries of Being Human and Big Data

Where the commercial, personal, and public interests are blurred, the highest ethical principles are going to be needed to ensure ‘abuse avoidance’ in the use of new technology, in increased data linkage and resultant data use in research of many different kinds.

How we as a society achieve the benefits of tech and datasharing and where its boundaries lie in “the public interest” needs public debate to co-design the direction we collectively want to partake in.

Once that is over, change needs supported by a method of oversight that is responsive to new technology, data use, and its challenges.

What a channel for ongoing public dialogue, challenge and potentially recourse might look like, should be part of that debate.

Destination smart-cities: design, desire and democracy (Part four)

Who is using all this Big Data? What decisions are being made on the back of it that we never see?

In the everyday and press it often seems that the general public does not understand data, and can easily be told things which we misinterpret.

There are tools in social media influencing public discussions and leading conversations in a different direction from that it had taken, and they operate without regulation.

It is perhaps meaningful that pro-reform Wellington School last week opted out of some of the greatest uses of Big Data sharing in the UK. League tables. Citing their failures. Deciding they werein fact, a key driver for poor educational practice.”

Most often we cannot tell from the data provided what we are told those Big Data should be telling us. And we can’t tell if the data are accurate, genuine and reliable.

Yet big companies are making big money selling the dream that Big Data is the key to decision making. Cumulatively through lack of skills to spot inaccuracy, and inability to do necessary interpretation, we’re being misled by what we find in Big Data.

Being misled is devastating for public trust, as the botched beginnings of care.data found in 2014. Trust has come to be understood as vital for future based on datasharing. Public involvement in how we are used in Big Data in the future, needs to include how our data are used in order to trust they are used well. And interpreting those data well is vital. Those lessons of the past and present must be learned, and not forgotten.

It’s time to invest some time in thinking about safeguarding trust in the future, in the unknown, and the unseen.

We need to be told which private companies like Cinven and FFT have copies of datasets like HES, the entire 62m national hospital records, or the NPD, our entire schools database population of 20 million, or even just its current cohort of 8+ million.

If the public is to trust the government and public bodies to use our data well, we need to know exactly how those data are used today and all these future plans that others have for our personal data.

When we talk about public bodies sharing data they hold for administrative purposes, do we know which private companies this may mean in reality?

The UK government has big plans for big data sharing, sharing across all public bodies, some tailored for individual interventions.

While there are interesting opportunities for public benefit from at-scale systems, the public benefit is at risk not only from lack of trust in how systems gather data and use them, but that interoperability gets lost in market competition.

Openness and transparency can be absent in public-private partnerships until things go wrong. Given the scale of smart-cities, we must have more than hope that data management and security will not be one of those things.

But how will we know if new plans design well, or not?

Who exactly holds and manages those data and where is the oversight of how they are being used?

Using Big Data to be predictive and personal

How do we definde “best use of data” in “public services” right across the board in a world in which boundaries between private and public in the provision of services have become increasingly blurred?

UK researchers and police are already analysing big data for predictive factors at postcode level for those at risk or harm, for example in combining health and education data.

What has grown across the Atlantic is now spreading here. When I lived there I could already see some of what is deeply flawed.

When your system has been as racist in its policing and equity of punishment as institutionally systemic as it is in the US, years of cumulative data bias translates into ‘heat lists’ and means “communities of color will be systematically penalized by any risk assessment tool that uses criminal history as a legitimate criterion.”

How can we ensure British policing does not pursue flawed predictive policies and methodologies, without seeing them?

What transparency have our use of predictive prisons and justice data?

What oversight will the planned new increase in use of satellite tags, and biometrics access in prisons have?

What policies can we have in place to hold data-driven decision-making processes accountable?<

What tools do we need to seek redress for decisions made using flawed algorithms that are apparently indisputable?

Is government truly committed to being open and talking about how far the nudge unit work is incorporated into any government predictive data use? If not, why not?

There is a need for a broad debate on the direction of big data and predictive technology and whether the public understands and wants it.If we don’t understand, it’s time someone explained it.

If I can’t opt out of O2 picking up my travel data ad infinitum on the Tube, I will opt out of their business model and try to find a less invasive provider. If I can’t opt out of EE picking up my personal data as I move around Hyde park, it won’t be them.

Most people just want to be left alone and their space is personal.

A public consultation on smart-technology, and its growth into public space and effect on privacy could be insightful.

Feed me Seymour?

With the encroachment of integrated smart technology over our cities – our roads, our parking, our shopping, our parks, our classrooms, our TV and our entertainment, even our children’s toys – surveillance and sharing information from systems we cannot see  start defining what others may view, or decide about us, behind the scenes in everything we do.

As it expands city wide, it will be watched closely if data are to be open for public benefit, but not invade privacy if “The data stored in this infrastructure won’t be confidential.”

If the destination of digital in all parts of our lives is smart-cities then we have to collectively decide, what do we want, what do we design, and how do we keep it democratic?

What price is our freedom to decide how far its growth should reach into public space and private lives?

The cost of smart cities to individuals and the public is not what it costs in investment made by private conglomerates.

Already the cost of smart technology is privacy inside our homes, our finances, and autonomy of decision making.

Facebook and social media may run algorithms we never see that influence our mood or decision making. Influencing that decision making is significant enough when it’s done through advertising encouraging us to decide which sausages to buy for your kids tea.

It is even more significant when you’re talking about influencing voting.

Who influences most voters wins an election. If we can’t see the technology behind the influence, have we also lost sight of how democracy is decided? The power behind the mechanics of the cogs of Whitehall may weaken inexplicably as computer driven decision from the tech companies’ hidden tools takes hold.

What opportunity and risk to “every part of government” does ever expanding digital bring?

The design and development of smart technology that makes decisions for us and about us, lies in in the hands of large private corporations, not government.

The means the public-interest values that could be built by design and their protection and oversight are currently outside our control.

There is no disincentive for companies that have taken private information that is none of their business, and quite literally, made it their business to not want to collect ever more data about us. It is outside our control.

We must plan by-design for the values we hope for, for ethics, to be embedded in systems, in policies, embedded in public planning and oversight of service provision by all providers. And that the a fair framework of values is used when giving permission to private providers who operate in public spaces.

We must plan for transparency and interoperability.

We must plan by-design for the safe use of data that does not choke creativity and innovation but both protects and champions privacy as a fundamental building block of trust for these new relationships between providers of private and public services, private and public things, in private and public space.

If “digital is changing how we deliver every part of government,” and we want to “harness the best of digital and technology, and the best use of data to improve public services right across the board” then we must see integration in the planning of policy and its application.

Across the board “the best use of data” must truly value privacy, and enable us to keep our autonomy as individuals.

Without this, the cost of smart cities growing unchecked, will be an ever growing transfer of power to the funders behind corporations and campaign politics.

The ultimate price of this loss of privacy, will be democracy itself.

****

This is the conclusion to a four part set of thoughts: On smart technology and data from the Sprint16 session (part one). I thought about this more in depth on “Smart systems and Public Services” here (part two), and the design and development of smart technology making “The Best Use of Data” here looking at today in a UK company case study (part three) and this part four, “The Best Use of Data” used in predictions and the Future.

Destination smart-cities: design, desire and democracy (Part three)

Smart Technology we have now: A UK Case Study

In places today, where climate surveillance sensors are used to predict and decide which smog-days cars should be banned from cities, automatic number-plate recognition (ANPR) can identify cars driving on the wrong days and send automatic penalties.

Similarly ANPR technology is used in our UK tunnels and congestion charging systems. One British company encouraging installation of ANPR in India is the same provider of a most significant part of our British public administrative data and surveillance softwares in a range of sectors.

About themselves that company says:

“Northgate Public Services has a unique experience of delivering ANPR software to all Home Office police forces. We developed and managed the NADC, the mission critical solution providing continuous surveillance of the UK’s road network.  The NADC is integrated with other databases, including the Police National Computer, and supports more than 30 million reads a day across the country.”

30 million snapshots from ‘continuous surveillance of the UK’s road network‘. That’s surprised me. That’s half the population in England, not all of whom drive. 30 million every day. It’s massive, unreasonable, and risks backlash.

Northgate Public Services’ clients also include 80% of UK water companies, as well as many other energy and utility suppliers.

And in the social housing market they stretch to debt collection, or ‘income management’.

So who I wondered, who is this company that owns all this data-driven access to our homes, our roads, our utilities, life insurance, hospital records and registeries, half of all UK calls to emergency services?

Northgate Information Solutions announced the sale of its Public Services division in December 2014 to venture capital firm Cinven. Cinven that also owns a 62% shareholding in the UK private healthcare provider Spire with all sorts of influence given their active share of services and markets. 

Not only does this private equity firm hold these vast range of data systems across a wide range of sectors, but it’s making decisions about how our public policies and money are being driven.

Using health screening data they’re even making decisions that affect our future and our behaviour and affect our private lives: software provides the information and tools that housing officers need to proactively support residents, such as sending emails, letters or rent reminders by SMS and freeing up time for face-to-face support.”

Of their ANPR systems, Northgate says the data should be even more widely used “to turn CONNECT: ANPR into a critical source of intelligence for proactive policing.”

If the company were to start to ‘proactively’ use all the data it owns across the sectors we should be asking, is ‘smart’ sensible and safe?

Where is the boundary between proactive and predictive? Or public and private?

Where do companies draw the line between public and personal space?

The public services provided by the company seem to encroach into our private lives in many ways, In Northgate’s own words, “It’s also deeply personal.”

Who’s driving decision making is clear. The source of their decision making is data. And it’s data about us.

Today already whether collected by companies proactively like ANPR or through managing data we give them with consent for direct administrative purpose, private companies are the guardians of massive amounts of our personal and public data.

What is shocking to me, is how collected data in one area of public services are also used for entirely different secondary purposes without informed consent or an FYI, for example in schools.

If we don’t know which companies manage our data, how can we trust that it is looked after well and that we are told if things go wrong?

Steps must be taken in administrative personal data security, transparency and public engagement to shore up public trust as the foundation for future datasharing as part of the critical infrastructure for any future strategy, for public or commercial application. Strategy must include more transparency of the processing of our data and public involvement, not the minimum, if ‘digital citizenship’ is to be meaningful.

How would our understanding of data improve if anyone using personal data were required to put in place clear public statements about their collection, use and analysis of data?  If the principles of data protection were actually upheld, in particular that individuals should be informed? How would our understanding of data improve especially regards automated decision making and monitoring technology? Not ninety page privacy policies. Plain English. If you need ninety pages, you’re doing too much with my data.

Independent privacy impact assessments should be mandatory and published before data are collected and shared with any party other than that to which it was given for a specific purpose. Extensions broadening that purpose should require consultation and consent. If that’s a street, then make it public in plain sight.

Above all, planning committees in local government, in policy making and practical application, need to think of data in every public decision they make and its ethical implications. We need some more robust decision-making in the face of corporate data grabs, to defend data collected in public space safe, and to keep some private.

How much less fun is a summer’s picnic spent smooching, if you feel watched? How much more anxious will we make our children if they’re not allowed to ever have their own time to themselves, and every word they type in a school computer is monitored?

How much individual creativity and innovation does that stifle? We are effectively censoring children before they have written a word.

Large corporations have played historically significant and often shadowy roles in surveillance that retrospectively were seen as unethical.

We should consider sooner rather than later, if corporations such as BAE systems, Siemens and the IMSs of the world act in ways worthy of our trust in such massive reach into our lives, with little transparency and oversight.

“Big data is big opportunity but Government should tackle misuse”

The Select Committee warned in its recent report on Big Data that distrust arising from concerns about privacy and security is often well-founded and must be resolved by industry and Government.

If ‘digital’ means smart technology in the future is used in “every part of government” as announced at #Sprint16, what will its effects be on the involvement and influence these massive corporations on democracy itself?

******

I thought about this more in depth on Part one here,  “Smart systems and Public Services” here (part two), and continue after this by looking at “The Best Use of Data” used in predictions and the Future (part four).

Destination smart-cities: design, desire and democracy (Part one)

When I drop my children at school in the morning I usually tell them three things: “Be kind. Have fun. Make good choices.”

I’ve been thinking recently about what a positive and sustainable future for them might look like. What will England be in 10 years?

The #Sprint16 snippets I read talk about how: ”Digital is changing how we deliver every part of government,” and “harnessing the best of digital and technology, and the best use of data to improve public services right across the board.”

From that three things jumped out at me:

  • The first is that the “best use of data” in government’s opinion may conflict with that of the citizen.
  • The second, is how to define “public services” right across the board in a world in which boundaries between private and public in the provision of services have become increasingly blurred.
  • And the third is the power of tech to offer both opportunity and risk if used in “every part of government” and effects on access to, involvement in, and the long-term future of, democracy.

What’s the story so far?

In my experience so far of trying to be a digital citizen “across the board” I’ve seen a few systems come and go. I still have my little floppy paper Government Gateway card, navy blue with yellow and white stripes. I suspect it is obsolete. I was a registered Healthspace user, and used it twice. It too, obsolete. I tested my GP online service. It was a mixed experience.

These user experiences are shaping how I interact with new platforms and my expectations of organisations, and I will be interested to see what the next iteration, nhs alpha, offers.

How platforms and organisations interact with me, and my data, is however increasingly assumed without consent. This involves new data collection, not only using data from administrative or commercial settings to which I have agreed, but new scooping of personal data all around us in “smart city” applications.

Just having these digital applications will be of no benefit and all the disadvantages of surveillance for its own sake will be realised.

So how do we know that all these data collected are used – and by whom? How do we ensure that all the tracking actually gets turned into knowledge about pedestrian and traffic workflow to make streets and roads safer and smoother in their operation, to make street lighting more efficient, or the environment better to breathe in and enjoy? And that we don’t just gift private providers tonnes of valuable data which they simply pass on to others for profit?

Because without making things better, in this Internet-of-Things will be a one-way ticket to power in the hands of providers and loss of control, and quality of life. We’ll work around it, but buying a separate SIM card for trips into London, avoiding certain parks or bridges, managing our FitBits to the nth degree under a pseudonym. But being left no choice but to opt out of places or the latest technology to enjoy, is also tedious. If we want to buy a smart TV to access films on demand, but don’t want it to pass surveillance or tracking information back to the company how can we find out with ease which products offer that choice?

Companies have taken private information that is none of their business, and quite literally, made it their business.

The consumer technology hijack of “smart” to always mean marketing surveillance creates a divide between those who will comply for convenience and pay the price in their privacy, and those who prize privacy highly enough to take steps that are less convenient, but less compromised.

But even wanting the latter, it can be so hard to find out how to do, that people feel powerless and give-in to the easy option on offer.

Today’s system of governance and oversight that manages how our personal data are processed by providers of public and private services we have today, in both public and private space, is insufficient to meet the values most people reasonably expect, to be able to live their life without interference.

We’re busy playing catch up with managing processing and use, when many people would like to be able to control collection.

The Best use of Data: Today

My experience of how the government wants to ‘best use data’ is that until 2013 I assumed the State was responsible with it.

I feel bitterly let down.

care.data taught me that the State thinks my personal data and privacy are something to exploit, and “the best use of my data” for them, may be quite at odds with what individuals expect. My trust in the use of my health data by government has been low ever since. Saying one thing and doing another, isn’t making it more trustworthy.

I found out in 2014 how my children’s personal data are commercially exploited and given to third parties including press outside safe settings, by the Department for Education. Now my trust is at rock bottom. I tried to take a look at what the National Pupil Database stores on my own children and was refused a subject access request, meanwhile the commercial sector and Fleet Street press are given out not only identifiable data, but ‘highly sensitive’ data. This just seems plain wrong in terms of security, transparency and respect for the person.

The attitude that there is an entitlement of the State to individuals’ personal data has to go.

The State has pinched 20 m children’s privacy without asking. Tut Tut indeed. [see Very British Problems for a translation].

And while I support the use of public administrative data in deidentified form in safe settings, it’s not to be expected that anything goes. But the feeling of entitlement to access our personal data for purposes other than that for which we consented, is growing, as it stretches to commercial sector data. However suggesting that public feeling measured based on work with 0.0001% of the population, is “wide public support for the use and re-use of private sector data for social research” seems tenuous.

Even so, comments even in that tiny population suggested, “many participants were taken by surprise at the extent and size of data collection by the private sector” and some “felt that such data capture was frequently unwarranted.” “The principal concerns about the private sector stem from the sheer volume of data collected with and without consent from individuals and the profits being made from linking data and selling data sets.”

The Best use of Data: The Future

Young people, despite seniors often saying “they don’t care about privacy” are leaving social media in search of greater privacy.

These things cannot be ignored if the call for digital transformation between the State and the citizen is genuine because try and do it to us and it will fail. Change must be done with us. And ethically.

And not “ethics” as in ‘how to’, but ethics of “should we.” Qualified transparent evaluation as done in other research areas, not an add on, but integral to every project, to look at issues such as:

  • whether participation is voluntary, opt-out or covert
  • how participants can get and give informed consent
  • accessibility to information about the collection and its use
  • small numbers, particularly of vulnerable people included
  • identifiable data collection or disclosure
  • arrangements for dealing with disclosures of harm and recourse
  • and how the population that will bear the risks of participating in the research is likely to benefit from the knowledge derived from the research or not.

Ethics is not about getting away with using personal data in ways that won’t get caught or hauled over the coals by civil society.

It’s balancing risk and benefit in the public interest, and not always favouring the majority, but doing what is right and fair.

We hear a lot at the moment on how the government may see lives, shaped by digital skills, but too little of heir vison for what living will look and feel like, in smart cities of the future.

My starting question is, how does government hope society will live there and is it up to them to design it? If not, who is because these smart-city systems are not designing themselves. You’ve heard of Stepford wives. I wonder what do we do if we do not want to live like Milton Keynes man?

I hope that the world my children will inherit will be more just, more inclusive, and with a more sustainable climate to support food, livelihoods and kinder than it is today. Will ‘smart’ help or hinder?

What is rarely discussed in technology discussions is how the service should look regardless of technology. The technology assumed as inevitable, becomes the centre of service delivery.

I’d like to first understand what is the central and local government vision for “public services”  provision for people of the future? What does it mean for everyday services like schools and health, and how does it balance security and our freedoms?

Because without thinking about how and who provides those services for people, there is a hole in the discussion of “the best use of data” and their improvement “right across the board”.

The UK government has big plans for big data sharing, sharing across all public bodies, some tailored for individual interventions.

While there are interesting opportunities for public benefit from at-scale systems, the public benefit is at risk not only from lack of trust in how systems gather data and use them, but that interoperability in service, and the freedom for citizens to transfer provider, gets lost in market competition.

Openness and transparency can be absent in public-private partnerships until things go wrong. Given the scale of smart-cities, we must have more than hope that data management and security will not be one of those things.

How will we know if new plans are designed well, or not?

When I look at my children’s future and how our current government digital decision making may affect it, I wonder if their future will be more or less kind. More or less fun.

Will they be left with the autonomy to make good choices of their own?

The hassle we feel when we feel watched all the time, by every thing that we own, in every place we go, having to check every check box has a reasonable privacy setting, has a cumulative cost in our time and anxieties.

Smart technology has invaded not only our public space and our private space, but has nudged into our head space.

I for one have had enough already. For my kids I want better. Technology should mean progress for people, not tyranny.

Living in smart cities, connected in the Internet-of-Things, run on their collective Big Data and paid for by commercial corporate providers, threatens not only their private lives and well-being, their individual and independent lives, but ultimately independent and democratic government as we know it.

*****

This is the start of a four part set of thoughts: Beginnings with smart technology and data triggered by the Sprint16 session (part one). I think about this more in depth in “Smart systems and Public Services” (Part two) here, and the design and development of smart technology making “The Best Use of Data” looking at today in a UK company case study (Part three) before thoughts on “The Best Use of Data” used in predictions and the Future (Part four).